Triple

T28334444
Position Surface form Disambiguated ID Type / Status
Subject Sawu Island E717626 entity
Predicate hasAlternativeName P39 FINISHED
Object Sabu Island
Sabu Island is a small, relatively arid island in eastern Indonesia’s East Nusa Tenggara province, known for its traditional weaving, distinct local culture, and subsistence agriculture.
E2120646 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sabu Island | Statement: [Sawu Island, hasAlternativeName, Sabu Island]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sabu Island
Triple: [Sawu Island, hasAlternativeName, Sabu Island]
Generated description
Sabu Island is a small, relatively arid island in eastern Indonesia’s East Nusa Tenggara province, known for its traditional weaving, distinct local culture, and subsistence agriculture.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69eff6e9a57c8190a69c2c74b5d72119 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64bd3f9288190ad68a1b7e7b0a76d completed May 2, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b248b6d8819083d6f2d1ecac346d completed June 21, 2026, 9:43 a.m.
NEDg Description generation batch_6a37b44d33708190bf09f5667351e546 completed June 21, 2026, 9:52 a.m.
NED2 Entity disambiguation (via description) batch_6a37b4aaf3b081909f052e9cdbfd5996 completed June 21, 2026, 9:53 a.m.
Created at: April 28, 2026, 12:34 a.m.